基于神经网络的HSIC改进算法分析与仿真

为提高控制系统的稳定性和优化控制性能.在对相平面e-e分析的基础上,提出了一种仿人智能控制(HSIC)特征模型的改进算法.将系统动态过程划分为若干运行模式,间接地与系统性能指标建立了相互联系.控制结构上采用开闭环(开环为主导的闭环控制),且控制模态简单.同时,将神经网络逆模型与HSIC相结合提出了一种新的智能控制器(神经网络复合HSIC控制器),将神经网络的参数自学习,自适应特性与HSIC控制相结合,降低了系统逆模型对原系统精确数学模型的依赖.仿真结果证明了设计方法的有效性.     

BP神经网络自抗扰控制器在套印系统中的应用

针对凹版印刷机套印纠偏系统参数变化范围大的特点,将神经网络嵌入到自抗扰控制器中,提出基于神经网络的自抗扰控制策略,并应用于凹版印刷机套印纠偏系统的控制中。对该控制器的结构及应用神经网络的训练样本、方法进行了分析和讨论。并得出了有益的结论。仿真结果表明,应用基于神经网络的自抗扰控制器较单一的自抗扰控制器具有参数适应性更大、动态特征更好等优点。     

Fuzzy Iterative Learning Control-based Design of Fault Tolerant Guaranteed Cost Controller for Nonlinear Batch Processes

International Journal of Control, Automation and Systems - For nonlinear batch processes with actuator faults and external disturbances, a fault-tolerant guaranteed cost controller is proposed...     

非线性PID控制器

本文利用非线性跟踪-微分器和非线性组合方式来改进经典PID调节器以提高其适应性和鲁棒性.     

区间系数不确定性系统的鲁棒控制器设计

本文提出了一种方法用于设计区间系数不确定性系统的鲁棒镇定控制器，所考虑的区间系数可以是时变的，控制器的设计仅依赖于区间系数的上下界，而设计步骤具有迭代特征。虽然所提到的控制器是线性和确定性的，但能够承受所有容允不确定性。所提出的方法通过一个电力系统负荷频率控制例子加以说明。     

A Novell Backstepping Nonlinear Controller Design for Nonlinear Vibration Systems

Introducing basic design methodology for developing backstepping nonlinear controller for vibration control system. With a simplified second-order system model of nonlinear vibration system (Duffing’s equation), where, the process has illustrated the backstepping design step-by-step. Backstepping is a novel nonlinear design tool, which is based on constructing the Lyapunov function for the closed-loop systems and guarantees the stability and tracking performance through energy dissipation. In general, this ...     

基于Backstepping方法的MIMO过程分散PID控制器设计

A novel decentralized PID controller design procedure based on backstepping principles is presented to operate multiple-input multiple-output (MIMO) dynamic processes. The first key feature of the design procedure is that a whole MIMO control system is decomposed into multiple control loops, therefore the sub-controllers can be efficiently flexibly designed in parallel prototype. The second key feature is that the decentralized controller has equivalency to those designed by backstepping approach. As a complementary support to the design procedure, the sufficient condition of the whole closed-loop system stability is analyzed via the small gain theorem and it can be proven that the process tracking performance is improved. The simulation results of the Shell benchmark control problem are provided to verify the effectiveness and practicality of the proposed decentralized PID control.     

Backstepping-based Decentralized PID Controller Design for MIMO Processes

A novel decentralized PID controller design procedure based on backstepping principles is presented to operate multiple-input multiple-output(MIMO)dynamic processes.The first key feature of the design procedure is that a whole MIMO control system is decomposed into multiple control loops,therefore the sub-controllers can be efficiently flexibly designed in parallel prototype. The second key feature is that the decentralized controller has equivalency to those designed by backstepping approach.As a complementary support to the design procedure,the sufficient condition of the whole closed-loop system stability is analyzed via the small gain theorem and it can be proven that the process tracking performance is improved.The simulation results of the Shell benchmark control problem are provided to verify the effectiveness and practicality of the proposed decentralized PID control.     

Twin Gaussian Processes for Structured Prediction

We describe twin Gaussian processes (TGP), a generic structured prediction method that uses Gaussian process (GP) priors on both covariates and responses, both multivariate, and estimates outputs by minimizing the Kullback-Leibler divergence between two GP modeled as normal distributions over finite index sets of training and testing examples, emphasizing the goal that similar inputs should produce similar percepts and this should hold, on average, between their marginal distributions. TGP captures not only the interdependencies between covariates, as in a typical GP, but also those between responses, so correlations among both inputs and outputs are accounted for. TGP is exemplified, with promising results, for the reconstruction of 3d human poses from monocular and multicamera video sequences in the recently introduced HumanEva benchmark, where we achieve 5 cm error on average per 3d marker for models trained jointly, using data from multiple people and multiple activities. The method is fast and automatic: it requires no hand-crafting of the initial pose, camera calibration parameters, or the availability of a 3d body model associated with human subjects used for training or testing.     

基于四元数的航天器姿态非线性控制器

针对由四元数描述的航天器姿态控制系统进行了非线性反馈控制器设计.首先,得到一类含角速度测量的反馈控制律.该控制律不仅可以保证闭环系统是全局渐近稳定的,而且保证了2个期望的平衡位置都是稳定的.然后,利用基于四元数的滤波器取代角速度测量,得到一类无需角速度测量的反馈控制律.该控制律同样保证了闭环系统的全局渐近稳定性和2个稳定的期望平衡位置.值得注意的是,2个稳定的期望平衡位置,将促使由任意初始姿态出发的轨迹都就近收敛至任意期望平衡位置.最后,数值仿真展示了所得反馈控制律的优势.     

一种非线性PD控制器设计

为了提高PD控制器的性能,提出了一种非线性设计方法。利用电容极间电场和PD控制器的控制作用之间存在的一些相似性,构造了一种非线性函数,并以此形成一种非线性PD控制器,这种控制器能为系统的运行状态提供灵活的增益策略;利用系统的运行状态信息,在相平面中实时旋转该电容结构,可以减少这种非线性PD控制器的设计参数。通过对一个机械手系统进行仿真,结果表明,这种控制方式能够获得较好的系统动态响应速度和参数鲁棒性能。     

离散区间系统鲁棒容错控制器的设计

讨论了离散线性系统的鲁棒容错控制问题.针对离散线性系统,当系统矩阵和控制矩阵存在参数区间摄动时,通过Lyapunov稳定性理论分析了系统同时存在传感器失效情况下的鲁棒稳定问题,给出了系统鲁棒稳定的一个充分条件,并在此基础上给出离散区间系统鲁棒容错控制器的设计方法.最后用数值算例解释了该算法的有效性.     

不平衡油耗数据的区间预测方法

对油耗数据进行区间预测时,数据的不平衡性会导致一般的区间预测方法得到的预测区间质量较低。针对上述问题,提出了基于SMOTE-XGBoost算法的区间预测模型。采用SMOTE算法增加训练集中少数类样本的数量,消除了训练集数据的不平衡性;对XGBoost算法的分位数损失函数进行改进,平滑其一阶导数原点周围的小区域,解决了分位数损失函数对树分裂的影响;通过训练区间预测模型,得到预测区间的上下界。最后基于QAR数据集进行对比实验,结果表明,该方法使预测区间具有较高的区间覆盖率和较窄的区间宽度,提高了预测区间的质量。     

区间矩阵系统低保守性鲁棒控制器的设计

对于系统矩阵和输入矩阵均为区间矩阵的不确定系统 ,提出了实对称矩阵集合的最小上界和最大下界的计算方法 ,并应用该方法设计区间矩阵系统鲁棒控制器 ,把确定多个矩阵不等式解的复杂问题简化为求解单代数Riccati矩阵方程 ,该设计方法具有较小保守性 .     

An analysis of model-based Interval Estimation for Markov Decision Processes

Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Interval Estimation (MBIE) learns efficiently in practice, effectively balancing exploration and exploitation. This paper presents a theoretical analysis of MBIE and a new variation called MBIE-EB, proving their efficiency even under worst-case conditions. The paper also introduces a new performance metric, average loss, and relates it to its less “online” cousins from the literature.     

GIS间隔控制器的研究与开发

研究基于IEC61850标准的GIS间隔控制器,阐述以ARM9微处理器为核心的GIS间隔控制器嵌入式硬件平台。以GIS间隔控制器的需求功能为依据、以IEC61850建模思想为指导,建立GIS间隔控制器的标准化信息模型。将GIS间隔控制器硬件作为载体,实现 GOOSE报文通信,使GIS间隔控制器具备符合IEC61850标准的过程层通信功能,完成GIS与间隔层保护、测量装置间开关位置信息和控制信息传输的数字化。通过GPS和报文分析工具搭建实验平台,结果证明,GIS控制器通信服务符合变电站装置智能化的设计需求。     

An Interval Entropy Penalty Method for Nonlinear Global Optimization

Entropy penalty functions have been successfully used in unconstrained and constrained nonlinear optimization problems. In this paper, we show that the interval majorant method can transform the entropy penalty method into an interval method that produces guaranteed results.     

卫星姿态跟踪的非线性PI控制器设计

针对刚体卫星的姿态跟踪问题,提出了一种新的非线性PI控制器。它不同于传统的全状态反馈控制方案,无需姿态角速度的测量信号,而是通过引入一个一阶低通滤波器来产生伪角速度信号,进而对其进行反馈。同时,采用积分控制以减少或抑制由于常值干扰力矩引起的常值姿态误差。通过Lyapunov方法分析证明了整个闭环系统是渐近稳定的。最后,仿真结果验证了所提出的输出反馈控制律在实现姿态跟踪和干扰抑制方面的有效性。     

非线性离散系统的自适应PID控制器

针对非线性离散系统设计了利用TSK(Takagi Sugeno Kang)模糊模型的自适应PID控制器。利用模糊模型预测控制信号误差,通过控制信号误差自适应PID控制器参数。比较系统输出和模糊模型输出自适应模糊模型的参数。该方法可以弥补系统参数的模糊性、数学模型的模型误差和系统参数的变化。非线性离散系统的仿真实验验证了所设计的自适应PID控制器对非线性离散系统控制的有效性。     

非线性CSTR过程预测控制器设计

针对非线性CSTR(continuously stirred tank reactor)过程,提出一种新的预测控制的设计与仿真实现.在对一类特殊非线性过程分析的基础上,从系统的输入输出数据出发,基于子空间辨识算法建立双线性系统模型来近似描述被控系统;设计新的预测控制算法实现对CSTR过程的跟踪控制;为补偿模型失配以消除控制中的稳态误差,将积分作用包含在预测控制器的设计中,实现对控制输出的良好跟踪性能;最后通过一个仿真实例验证算法的有效性.